Blind Channel Estimation of Doubly Selective Fading Channels

  • Jinfeng Tian
  • Ting Zhou
  • Tianheng Xu
  • Honglin Hu
  • Mingqi LiEmail author
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 262)


Blind channel identification methods based on second-order statistics (SOS), have attracted much attention in the literature. However, these estimators suffer from the phase ambiguity problem, until additional diversity can be exploited. In this paper, with the aid of the cyclic prefix (CP) induced periodicity, a channel identification algorithm based on the time varying autocorrelation function (TVAF) is proposed for doubly selective fading channels in Orthogonal Frequency Division Multiplexing (OFDM) systems. The closed-form expression for time-varying channel identification is derived within the restricted support set of time index. Particularly, the CP-induced TVAF components and their corresponding channel-spread correlation elements implicitly carry rich channel information and are not perturbed by additive noise. These advantageous peaks can be employed to address the phase uncertainty problem, offering an alternative way of increasing the rank of signal matrix to achieve complementary diversity. Simulation results demonstrate the proposed method can provide distinctly higher accurate of channel estimation over the classical scheme.


Channel estimation Doubly selective fading channels Time-varying autocorrelation function Subspace 


  1. 1.
    Wu, Q., Liang, Q.: Higher-order statistics in co-prime sampling with application to channel estimation. IEEE Trans. Wirel. Commun. 14(12), 6608–6620 (2015)CrossRefGoogle Scholar
  2. 2.
    Yu, C., Xie, L., Zhang, C.: Deterministic blind identification of IIR systems with output-switching operations. IEEE Trans. Signal Process. 62, 1740–1749 (2014)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Giannakis, G.B., Tepedelenlioglu, C.: Basis expansion models and diversity techniques for blind identification and equalization of time-varying channels. Proc. IEEE 86(10), 1969–1986 (1998)CrossRefGoogle Scholar
  4. 4.
    Bonna, K., Spasojevic, P., Kanterakis, E.: Subspace-based SIMO blind channel identification: asymptotic performance comparison. In: Proceedings - IEEE Military Communications Conference, pp. 460–465 (2016)Google Scholar
  5. 5.
    Ghauch, H., Kim, T., Bengtsson, M., Skoglund, M.: Subspace estimation and decomposition for large millimeter-wave MIMO systems. IEEE J. Sel. Top. Signal Process. 10(3), 528–542 (2016)CrossRefGoogle Scholar
  6. 6.
    Mayyala, Q., Abed-Meraim, K., Zerguine, A.: Structure-based subspace method for multichannel blind system identification. IEEE Signal Process. Lett. 24(8), 1183–1187 (2017)CrossRefGoogle Scholar
  7. 7.
    Tsatsanis, M.K., Giannakis, G.B.: Subspace methods for blind estimation of time-varying FIR channels. IEEE Trans. Signal Process. 45, 3084–3093 (1997)CrossRefGoogle Scholar
  8. 8.
    Champagne, B., El-Keyi, A., Tu, C.-C.: A subspace method for the blind identification of multiple time-varying FIR channels. In: Proceedings of IEEE Global 2009, pp. 1–6. Honolulu, HI (2009)Google Scholar
  9. 9.
    Tian, Y.: Subspace method for blind equalization of multiple time-varying FIR channels, Master’s Thesis. McGill University (2012)Google Scholar
  10. 10.
    Fang, S.-H., Lin, J.-S.: Analysis of two-step subspace-based channel estimation method for OFDM systems. In: Proceedings of IEEE VTC Spring, pp. 1–5. Sydney, Australia, 4–7 June 2017Google Scholar
  11. 11.
    Napolitano, A.: Cyclostationarity: New trends and applications. Signal Process. 120, 385–408 (2016)CrossRefGoogle Scholar
  12. 12.
    Tian, J., Guo, H., Hu, H., Yang, Y.: OFDM signal sensing over doubly-selective fading channels. In: Proceedings of IEEE GLOBECOM, pp. 1–5. Miami, USA, 7–9 Dec 2010Google Scholar
  13. 13.
    Tian, J., Jiang, Y., Hu, H.: Cyclostationarity-based frequency synchronization for OFDM systems over doubly-selective fading channels. Wirel. Pers. Commun. 66(2), 461–472 (2012)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  • Jinfeng Tian
    • 1
  • Ting Zhou
    • 1
  • Tianheng Xu
    • 1
  • Honglin Hu
    • 1
  • Mingqi Li
    • 1
    Email author
  1. 1.Shanghai Advanced Research Institute (SARI)Chinese Academy of Science (CAS)BeijingChina

Personalised recommendations